1. Field of the Invention
The present invention relates to a technology to detect static or moving obstacle, particularly to a self-adaptive image-based obstacle detection method that filters out the background to obtain the position of an obstacle.
2. Description of the Related Art
Most conventional image-based obstacle detection methods use the edge detection technology or the image flow technology to detect the region of a moving object, and then use a mathematical morphological method to find possible positions of the object, and then use a shape matching technology to search in different regions to determine which one is an obstacle or a moving obstacle. The discrimination ability depends on the adaptability of the templates. If the templates are insufficient, probability of error increases, and the search time is prolonged. Some conventional image-based obstacle detection methods calculate the image eigenvalues of the possible moving objects in an image and construct a logic mechanism to determine whether one possible moving object is a real moving object. However, the conventional technology is time-consuming and hard to implant into an embedded system.
A Taiwan patent No. I327536 disclosed an edge-based obstacle detection method, which comprises steps: capturing a plurality of original images; extracting edges from the original images to generate edge objects and the information corresponding to each edge object; regulating the focus length of the camera and the horizontal distance according to the information of the edge objects; generating the relative distance of each edge object; comparing the relative distance of each edge object with a threshold distance; determining an edge object to be an obstacle if its relative distance is less than the threshold distance. However, the discrimination ability of the prior art depends on the adaptability of the templates. If the templates are insufficient, the probability of error increases, and the search time is prolonged.
A U.S. Pat. No. 7,346,191 disclosed an image flow-based obstacle detection method, which converts the image flows of the captured obstacle images into histograms to find out obstacles. The prior art is also an obstacle detection method. However, it is distinct from the abovementioned methods that compare the background with the image of the possible obstacle to find out a moving obstacle. The prior art needs complicated computation and thus has poor efficiency.
Accordingly, the present invention proposes a self-adaptive image-based obstacle detection method to solve the above-mentioned problems.